Tariq et al. BMC Medicine(2020) 18:166
https://doi.org/10.1186/s12916-020-01615-9

RESEARCH ARTICLE

Open Access

Real-time monitoring the transmission
potential of COVID-19 in Singapore,
March 2020
Amna Tariq1*, Yiseul Lee1, Kimberlyn Roosa1, Seth Blumberg2, Ping Yan3, Stefan Ma4 and Gerardo Chowell1

Abstract
Background: As of March 31, 2020, the ongoing COVID-19 epidemic that started in China in December 2019 is
now generating local transmission around the world. The geographic heterogeneity and associated intervention
strategies highlight the need to monitor in real time the transmission potential of COVID-19. Singapore provides aunique case example for monitoring transmission, as there have been multiple disease clusters, yet transmission
remains relatively continued.
Methods: Here we estimate the effective reproduction number, Rt, of COVID-19 in Singapore from the publicly
available daily case series of imported and autochthonous cases by date of symptoms onset, after adjusting the
local cases for reporting delays as of March 17, 2020. We also derive the reproduction number from the distributionof cluster sizes using a branching process analysis that accounts for truncation of case counts.
Results: The local incidence curve displays sub-exponential growth dynamics, with the reproduction number
following a declining trend and reaching an estimate at 0.7 (95% CI 0.3, 1.0) during the first transmission wave by
February 14, 2020, while the overall R based on the cluster size distribution as of March 17, 2020, was estimated at
0.6 (95% CI 0.4, 1.02). The overall mean reporting delay was estimated at 6.4 days (95% CI 5.8, 6.9), but it was shorter
among imported cases compared to local cases (mean 4.3 vs. 7.6 days, Wilcoxon test, p < 0.001).
Conclusion: The trajectory of the reproduction number in Singapore underscores the significant effects ofsuccessful containment efforts in Singapore, but it also suggests the need to sustain social distancing and active
case finding efforts to stomp out all active chains of transmission.
Keywords: SARS-CoV-2, COVID-19, Singapore, Transmission potential, Transmission heterogeneity, Reproduction
number, Cluster distribution, Reporting delay

Background
The ongoing Coronavirus Disease 2019 (COVID-19) pandemic started with a cluster of pneumonia cases of unknown
etiology in Wuhan, China, back in December 2019 [1, 2].
The initial cases have been linked to a wet market in the cityof Wuhan, pointing to an animal source of the epidemic [3].
* Correspondence: atariq1@student.gsu.edu
1
Department of Population Health Sciences, School of Public Health, Georgia
State University, Atlanta, GA 30303, USA
Full list of author information is available at the end of the article

Subsequently, rapid human-to-human transmission of thedisease was confirmed in January 2020, and the etiologicalagent was identified as severe acute respiratory syndromerelated coronavirus 2 (SARS-CoV-2) due to its genetic similarity to the SARS-CoV (severe acute respiratory syndrome
coronavirus) discovered in 2003 [4, 5]. The total global casetally has reached 750,890 infections including 36,405 deaths
and involving 199 countries as of March 31, 2020 [6]. As thevirus continues to spread in the human population, obtaining
an accurate “real-time” picture of the epidemic’s trajectory is© The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License,
which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give
appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate ifchanges were made. The images or other third party material in this article are included in the article's Creative Commonslicence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commonslicence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain
permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to thedata made available in this article, unless otherwise stated in a credit line to the data.

Tariq et al. BMC Medicine(2020) 18:166

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complicated by several factors including reporting delays andchanges in the case definition [7, 8]. Although the COVID19 case incidence in China has substantially declined, active
transmission is now occurring in multiple countries aroundthe world [2]. Epidemiological data from these countries canhelp to monitor transmission potential of SARS-CoV-2 innear real time.
Outside of China, Singapore, where the first symptomatic imported case (66 years old Chinese male) was reported on January 23, 2020, has been able to maintainrelatively low COVID-19 incidence levels through active
case finding and strict social distancing measures. Up until
March 31, 2020, Singapore has reported 926 laboratory
confirmed cases, including 24 reported case importations
from Wuhan China and 501 non-Wuhan-related case importations [9]. Imported cases include six individuals who
were evacuated from China between January 30 and February 9, 2020, and multiple citizens and long-term
Singapore pass holders returning from Asia, Europe, andNorth America in late March 2020 [9–11]. Moreover,
Singapore has reported 3 deaths as of March 31, 2020 [9].
On February 4, 2020, the Ministry of Health of Singapore
reported its first local cluster of COVID-19, which was
linked to the Yong Thai Hang shop [12]. A total of 18
clusters with 2 or more COVID-19 cases have been reported thus far. Table 1 summarizes the characteristics of
the 6 largest clusters in Singapore.
Although large-scale community transmission has notbeen reported in Singapore, the novel coronavirus canrapidly spread in confined and crowded places, as illustrated by large clusters of COVID-19 cases linked to theGrace Assembly of God Church, the Life Church andMissions Singapore, Wizlearn Technologies, and the
SAFRA Jurong cluster [13, 14]. In China, substantial
hospital-based transmission of SARS-CoV-2 has beenreported, with approximately 3400 cases involving
healthcare workers [15]. This pattern aligns well withpast outbreaks of severe acute respiratory syndrome(SARS) and Middle Eastern respiratory syndrome(MERS) [16], including substantial nosocomial transmission during the 2003 SARS outbreak in Singapore [17]. To
minimize the risk of hospital-based transmission of SARSCoV-2, the Ministry of Health of Singapore has restricted
the movement of patients and staff across hospitals [18].
Also, because multiple unlinked COVID-19 cases havebeen reported in the community [19] and the recognition
that a substantial proportion of asymptomatic cases may
be spreading the virus [20–22], strict social distancing
measures have been put in place including advising the
public against large social gatherings in order to mitigate
the risk of community transmission [23]. These social distancing measures reduce the risk of onward transmission
not only within Singapore, but also beyond the borders of
this highly connected nation [24]. A recent influx ofimported cases from Asia, Europe, and North America
into Singapore has triggered travel bans and restrictions
for travelers and citizens [9].
The reproduction number is a key threshold quantity toassess the transmission potential of an emerging diseasesuch as COVID-19 [25, 26]. It quantifies the average number of secondary cases generated per case. If the
reproduction number is below 1.0, infections occur in isolated clusters as self-limited chains of transmission, andpersistence of the disease would require continued undetected importations. On the other hand, reproduction
numbers above 1.0 indicate sustained community transmission [16, 26]. Using epidemiological data and mathematical modeling tools, we are monitoring the effective
reproduction number, Rt, of SARS-CoV-2 transmission in
Singapore in real-time, and here we report the evolution

Table 1 Characteristics of the largest COVID-19 outbreak in Singapore as of March 17, 2020
Cluster name

Cluster location

Clustersize

Number ofimportedcases linked tothe cluster

Number of
local cases
linked to theclusterNumber ofsecondarycases in thecluster

Reporting date
for the firstcase linked tocluster

Reporting date
for the lastcase linked tocluster

Yong Thai Hang
cluster

Yong Thai Hang Medical Store on
Cavan Road

9

0

9

1

February 4,
2020

February 8,
2020

Grand Hyatt cluster

Grand Hyatt hotel in Orchard

3

0

3

0

February 6,
2020

February 8,
2020

The Life Church andMissions and The
Grace Assembly of
God cluster

The Life Church and Missions at
Paya Lebar and The Grace
Assembly of God Church at
Tanglin and Bukit Batok

33

2

31

10

January 29,
2020

March 9, 2020

Seletar Aerospace
Heights construction
cluster

Seletar Aerospace Heights
construction site

5

0

5

4

February 9,
2020

February 15,
2020

WizlearnTechnologies cluster

Wizlearn Technologies in Science
park

14

0

14

8

February 26,
2020

March 3, 2020

48

0

48

29

February 27,
2020

March 16,
2002

SAFRA Jurong cluster SAFRA Jurong restaurant

Tariq et al. BMC Medicine(2020) 18:166

of Rt by March 17, 2020. Specifically, we characterize thegrowth profile and the effective reproduction number during the first transmission wave from the daily case seriesof imported and autochthonous cases by date of symptoms onset after adjusting for reporting delays, and we
also derive an estimate of the overall reproduction number
based on the characteristics of the clusters of COVID-19
in Singapore.

Methods

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cluster had left Singapore before the onset of symptoms.
All Singaporean residents associated with this cluster
have recovered as of February 19, 2020 [30]. No additional cases have been added to this cluster as of February 8, 2020.
Seletar Aerospace Heights cluster

This cluster with 5 Bangladeshi work pass holders was
identified on February 9, 2020. No further cases havebeen added to this cluster as of February 15, 2020.

Data

We obtained the daily series of 247 confirmed COVID19 cases in Singapore between January 23 and March 17,
2020, from public records of the Ministry of Health,Singapore, as of March 17, 2020 [27]. Individual-level
case details including the dates of symptom onset, thedate of reporting, and whether the case is autochthonous(local transmission) or imported are publicly available.
Clusters consisting of two or more cases according to
the infection source were also assembled from case descriptions obtained from field investigations conductedby the Ministry of Health, Singapore [27]. Single
imported cases are analyzed as clusters of size 1 whereas
unlinked cases were excluded from the cluster analysis.
Transmission clusters

As of March 17, 2020, 18 different clusters of COVID19 cases with 2–48 cases per cluster have been reported
in Singapore. A schematic diagram and characteristics of
the COVID-19 clusters in Singapore are given in Fig. 1
and Table 1. The geographic location of the six clusters
accounting for 45.3% of the total cases is shown in Fig. 2
whereas the corresponding distribution of cluster sizes isshown in Fig. 3.

The Life Church and Missions and The Grace Assembly of
God cluster

This Singaporean cluster is composed of 33 cases, including two imported cases and 31 local cases. The cluster started during The Life Church and Missions service
event in Paya Lebar on January 19, 2020. This event wasapparently seeded by two visitors from Wuhan China
who infected a couple with SARS-CoV-2 at the church.
The infected couple likely passed the infection to another case during a Lunar New Year’s celebration on
January 25, 2020. This case had subsequently infected
Grace Assembly of God church staff at the Tanglin
branch, generating secondary cases by the time he
was reported on February 14, 2020. Two branchesof the Grace Assembly of God church at Tanglin
and Bukit Batok have been included in this cluster[28, 31]. This church serves an average of 4800
people in attendance over the weekend. While thechurch has momentarily closed, field investigations
have not led to conclusive evidence regarding superspreading transmission. No further cases have been
added to this cluster as of March 9, 2020.
SAFRA Jurong cluster

Yong Thai Hang cluster

This cluster with 9 cases was the first to be reported in
Singapore. It has nine traceable links, including eight
Chinese and one Indonesian national associated with thevisit of Chinese tourists to the Yong Thai Hang healthproducts store, a shop that primarily serves the Chinese
population, on January 23, 2020. Four shop employees
and the tour guide were first identified as a cluster on
February 4, 2020 [12, 28, 29]. The tour guide subsequently infected her husband, a newborn, and the domestic helper [29]. No further cases have been added tothis cluster as of February 8, 2020.

The largest cluster composed of 48 local cases is linked
to a private dinner function at SAFRA Jurong restaurant
on February 15, 2020. The restaurant was closed forcleaning from February 16 to February 19, 2020, following the dinner function. The latest case was added tothis cluster on March 16, 2020.
Wizlearn Technologies cluster

This cluster which comprises of 14 cases was identified
on February 26, 2020. Wizlearn Technologies is ane-learning solutions company. The latest case was added
to this cluster on March 3, 2020.

Grand Hyatt hotel

Church of Singapore cluster

This cluster with 3 local cases was the second cluster toreceive international attention, as it originated from abusiness meeting held at the Grand Hyatt hotel attended
by Singaporean locals and the Chinese visitors from
Hubei [30]. Four international cases associated with thisThe first case of this cluster was identified on March 14,
2020, originating as a secondary case from a case in the
SAFRA Jurong cluster. This cluster is composed of 3
local cases. No further cases have been added to thiscluster since March 16, 2020.

Tariq et al. BMC Medicine(2020) 18:166

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Fig. 1 Cluster network of the cases in Singapore for the COVID-19 global pandemic as of March 17, 2020. The pink circles represent
the cases linked to Wuhan, the green circles represent the non-Wuhan-related case importations, and the blue circles represent caseswith no travel history to China. The larger dotted circles represent the COVID-19 disease clusters. Each blue arrow represents the
direction in which the disease was transmitted. Pink arrows represent immediate family. Dates below the circles are the dates ofcase reporting

Boulder gym cluster

The first case of this cluster was identified on
March 8, 2020, also linked to the SAFRA Jurong

cluster. This cluster is composed of 3 local cases.
No further cases have been added to this cluster
since March 10, 2020.

Tariq et al. BMC Medicine(2020) 18:166

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Fig. 2 Map depicting the spatial distribution of the 6 largest COVID-19 clusters in Singapore; Grand Hyatt cluster, Yong Thai Hang cluster, Seletar
Aerospace cluster, Wizlearn Technologies cluster, SAFRA Jurong cluster, and The Grace Assembly of God Church and Life Church and Missions
cluster as of March 17, 2020

Fig. 3 Distribution of COVID-19 cluster sizes in Singapore as of March 17, 2020

Tariq et al. BMC Medicine(2020) 18:166

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Cluster A

Cluster J

The first case of this cluster was identified on February
14, 2020. The cluster comprises of 3 local cases. No further cases have been added in this cluster as of February
18, 2020.

The first case of this cluster was identified on March 15,
2020. This cluster is composed of one imported and one
local case. No further cases have been added to this cluster since March 16, 2020.

Cluster B

Adjusting for reporting delays

The first case of this cluster was identified on February
19, 2020. This cluster is composed of two local cases.
No further cases have been added in this cluster since
February 21, 2020.

As an outbreak progresses in real time, epidemiologicalcurves can be distorted by reporting delays arising fromseveral factors that include (i) delays in case detection
during field investigations, (ii) delays in symptom onset
after infection, (iii) delays in seeking medical care, (iv)delays in diagnostics, and (v) delays in processing data insurveillance systems [32]. However, it is possible to generate reporting-delay-adjusted incidence curves using
standard statistical methods [33]. Briefly, the reporting
delay for a case is defined as the time lag in days between the date of onset and date of reporting. Here we
adjusted the COVID-19 epidemic curve of local cases byreporting delays using a non-parametric method that
employs survival analysis known as the Actuaries
method for use with right truncated data, employing reverse time hazards to adjust for reporting delays as described in a previous publication [34–36]. The 95%
prediction limits are derived according to Lawless andKalbfleisch [37]. For this analysis, we exclude 7 imported
cases and 5 local cases for which dates of symptoms onset are unavailable.

Cluster C

This first case of this cluster was identified on March 3,
2020. This cluster is composed of 2 local cases. No further cases have been added to this cluster since March
6, 2020.
Cluster D

The first case of this cluster was identified on March 7,
2020. The two cases (one imported and one local) in thiscluster are related to each other. No further cases havebeen added in this cluster since March 8, 2020.
Cluster E

The two cases (an imported and a local case) of thiscluster were identified on March 11, 2020. No further
cases have been added in this cluster since March 11,2020.

Effective reproduction number from case incidence
Cluster F

The first case of this cluster was identified on March 11,
2020. This cluster is composed of 3 local cases. No further cases have been added to this cluster since March
13, 2020.
Cluster GThis cluster is composed of 5 cases, including 4
imported cases. The first case of this cluster was identified on March 10, 2020. No further cases have been
added to this cluster since March 13, 2020.
Cluster H

The first case of this cluster was identified on March 14,
2020, a secondary case generated from a case at SAFRA
Jurong cluster. This cluster is composed of 3 local cases.
No further cases have been added to this cluster since
March 16, 2020.
Cluster I

The first case of this cluster was identified on March 14,
2020. This cluster is composed of one local and one
imported case. No further cases have been added to thiscluster since March 15, 2020.

We assess the effective reproduction number over thecourse of the outbreak, Rt, which quantifies the temporalvariation in the average number of secondary cases generated per case during the course of an outbreak after
considering multiple factors including behavior changes,
cultural factors, and the implementation of public healthmeasures [16, 26, 38]. Estimates of Rt > 1 indicate sustained transmission, whereas, Rt < 1 implies that the outbreak is slowing down and the incidence trend isdeclining. Hence, maintaining Rt < 1 is required to bringan outbreak under control. Using the reporting delay adjusted incidence curve, we estimate the most recent estimate of Rt for COVID-19 in Singapore by characterizing
the early transmission phase using a phenomenological
growth model as described in previous publications [39–42]. Specifically, we first characterize daily incidence of
local cases for the first transmission wave (January 21–
February 14, 2020) using the generalized logistic growthmodel (GLM) after adjusting for imported cases. Thismodel characterizes the growth profile via three parameters: the growth rate (r), the scaling of the growth parameter (p), and the final epidemic size (K). The GLM
can reproduce a range of early growth dynamics, including constant growth (p = 0), sub-exponential or

Tariq et al. BMC Medicine(2020) 18:166

polynomial growth (0 < p < 1), and exponential growth(p = 1) [40, 42]. We denote the local incidence at calendar time ti by Ii, the raw incidence of imported cases atcalendar time ti by Ji, and the discretized probability distribution of the generation interval by ρi. The generationinterval is assumed to follow a gamma distribution witha mean of 4.41 days and a standard deviation of 3.17 days
based on refs. [43, 44]. Then, we can estimate the effective reproduction number by employing the renewal
equation given by [45, 46]Ii
I
j¼0 i− j þ α J i− j ρi

Rti ¼ Pi

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infections being unobserved. This is accomplished by denoting x as the sum of the observed number of serial intervals in a cluster. Then the likelihood that an observed
cluster of size j containing m imported cases is generated by x infectious intervals is given by:
lCm→ j ðReff ; k; xÞ ¼

mlx→ð j−mÞ ðReff ; k Þjð1Þwhere the likelihood of i infections causing j infections
is given by:

In this equation, the numerator represents the newcases Ii, and the denominator represents the total number of cases that contribute to the new cases Ii at time ti.
Parameter 0 ≤α ≤ 1 represents the relative contributionof imported cases to the secondary disease transmission.
We perform a sensitivity analyses by setting α = 0.15 andα = 1.0 [47]. Next, in order to derive the uncertainty
bounds around the curve of Rt directly from the uncertainty associated with the parameters estimates (r, p, K),
we estimate Rt for 300 simulated curves assuming a
Poisson error structure [48].
Reproduction number (R) from the analysis of clustersizes

A second method of inferring the reproduction number
applies branching process theory to cluster size data toinfer the degree of transmission heterogeneity [49, 50].
Simultaneous inference of heterogeneity and the
reproduction number has been shown to improve thereliability of confidence intervals for the reproduction
number [51]. In the branching process analysis, thenumber of transmissions caused by each new infection ismodeled as a negative binomial distribution. This is parameterized by the effective reproduction number, R,
and the dispersion parameter, k. The reproduction number provides the average number of secondary cases per
index case, and the dispersion parameter varies inverselywith the heterogeneity of the infectious disease. In thisparameterization, a lower dispersion parameter indicateshigher transmission heterogeneity.
Branching process theory provides an analytic representation of the size distribution of cluster sizes as afunction of R, k, and the number of primary infections
in a cluster (as represented in equation of 6 of the supplement of [52]). This permits direct inference of the
maximum likelihood estimate and confidence interval
for R and k. In this manuscript, we modify the calculation of the likelihood of a cluster size to account for the
possibility that truncation of case counts at a specifictime point (i.e., March 17, 2020) may result in someli→ j ðReff ; k Þ ¼

Γð j þ kiÞΓð j þ 1ÞΓðkiÞkReff þ k

ki 

Reff
Reff þ kjð2Þwhere Γ is the gamma function.
To determine the number of observed serial intervals
in each cluster, we first estimate the cumulative probability distribution of the serial interval. We assume theserial interval is a gamma distribution, with a mean of
4.7 days and a standard deviation of 2.9 days [43]. Thistranslates to a shape parameter of 2.63 and a scale parameter of 1.79. We then use the difference between theonset data and the end of our study (March 17, 2020) to
determine how much of the infectious period was observed. For cases that only have a report date, but no onset date, we assume an onset date that is 6 days earlier
than the reporting date. This is based on the average
duration between onset date and report date that wasobserved in the data. When applied to the case series,
we are able to assign a total size, the number ofimported cases, and the observed number of infectious
periods for each cluster in the case series. When no
imported cases are known to be in a cluster, we assign
the number of imported cases to be one as the cluster
must have been initiated by someone (e.g., the index
case had contact with a foreign visitor).
When Eq. (1) is applied to the table of cluster size
characteristics, the likelihood of the data can be calculated as a function of R and k. Minimizing the likelihood
produces the maximum likelihood estimates of R and k.
Applying the likelihood ratio test by profiling and R and
k produces confidence intervals [53]. Code was run in R
version 3.6.1.

Results
Incidence data and reporting delays

The COVID-19 epidemic curve by the date of reporting,stratified for local and imported incidence case counts,
is shown in Fig. 4. It shows that the majority of theimported cases are concentrated at the beginning of theoutbreak (January 23, 2020 to February 3, 2020) andTariq et al. BMC Medicine(2020) 18:166

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Fig. 4 Local and imported incidence cases by date of reporting as of March 17, 2020. The solid blue line represents the cumulative case countfor the COVID-19 cases in Singapore

after March 10, 2020, in Singapore, with an average of~12 new cases reported per day between March 1, 2020,
and March 17, 2020 (Fig. 4). Out of 88 imported cases,
only 14 cases have been linked to secondary cases.
Meanwhile, a total of 159 autochthonous cases havebeen reported as of March 17, 2020, including 27 casesthat are unlinked to any known transmission chains.
The reporting-delay adjusted epidemic curve of local
cases by date of symptoms onset roughly displays two
small waves of transmission reflecting the occurrence ofasynchronous case clusters (Fig. 5). Moreover, thegamma distribution provided a reasonable fit to the distribution of reporting delays for all cases, with a mean
reporting delay at 6.4 days (95% CI 5.8, 6.9) (Fig. 6). We
also found that imported cases tend to have shorter
reporting delays compared to local cases (mean 4.3 vs.
7.6 days, Wilcoxon test, p < 0.001), as imported cases
tend to be identified more quickly. The mean of reporting delays for the six large clusters ranged from 4.8 to
13.6 days (Fig. 7).

the scaling of growth parameter p at 0.7 (95% CI 0.4,1.0), the intrinsic growth rate r estimated at 0.6 (95% CI
0.3, 1.1) and parameter K estimating the wave size estimated at 95 (95% CI 56, 230). Because of the subexponential growth dynamics, the effective reproduction
number followed a declining trend with the latest estimate at 0.7 (95% CI 0.3, 1.0) when α = 0.15 (Fig. 8). Thisestimate was not sensitive to changes in parameter α.
Based on the entire distribution of cluster sizes, we
jointly estimated the overall reproduction number R andthe dispersion parameter k as of March 17, 2020. Fitting
the negative binomial distribution to the cluster data inthe empirical distributions of the realizations during theearly stages of the outbreak in Singapore, the reproduction
number is estimated at 0.61 (95% CI 0.39, 1.02) after
adjusting for the truncation of the time series leading to
the possibility that some infected cases might still cause
new infections after March 17, 2020. The dispersion parameter is estimated at 0.11 (95% CI 0.05, 0.25) consistent
with SARS-CoV-2 transmission heterogeneity.

Reproduction numbers

Discussion
Overall, current estimates of transmission potential in
Singapore, based on two different data sources and different
methods, suggest that temporary local transmission

For the first small wave of transmission comprising thefirst 25 epidemic days, the delay-adjusted local incidence
curve displays sub-exponential growth dynamics with

Tariq et al. BMC Medicine(2020) 18:166

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Fig. 5 Reporting delay adjusted local incidence for the COVID-19 outbreak in Singapore as of March 17, 2020. Blue bars represent the raw
incidence, red solid line represents the adjusted incidence, and red dotted lines represent the 95% lower and upper bound of theadjusted incidence

potential of SARS-CoV-2 has occurred in Singapore while
our most recent estimate of the effective reproduction
number is below the epidemic threshold of 1.0 whereas theoverall reproduction number derived from the distributionof cluster sizes just barely crosses 1.0 (R = 0.61 (95% CI
0.39, 1.02). Temporary sustained transmission in the beginning of the epidemic can be partly attributed to multiple

case importations and initiation of local transmission in theregion. While large-scale local transmission has not beenreported in Singapore, the fact that asymptomatic and subclinical cases are now well documented for COVID-19 [54]suggests that our estimates could be underestimated [55].
On the other hand, it is not clear if asymptomatic or subclinical cases are as infectious as symptomatic cases. Indeed,

Fig. 6 The distribution of reporting delays for all cases as of March 17, 2020. The red line represents the fit of a gamma distribution to the data.
The red circle represents the mean of gamma distribution and the horizontal line represents the 95% CI

Tariq et al. BMC Medicine(2020) 18:166

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Fig. 7 Reporting delay distribution with mean (blue circle) and 95% CI (vertical lines) for each big cluster in Singapore; Grand Hyatt cluster, Yong
Thai Hang cluster, Seletar Aerospace cluster, Wizlearn Technologies cluster, SAFRA Jurong cluster, and The Grace Assembly of God Church andLife Church and Missions cluster as of March 17, 2020

we have reported that multiple local cases have yet to be
traced to existing transmission chains [9]. Additional datacollected during the course of the outbreak will help obtain an improved picture of the transmission dynamics.
These findings emphasize the need to strengthen publichealth interventions including active case contact tracing
activities in countries with emerging transmission of

SARS-CoV-2 [56]. It is worth noting that imported cases
have minor contribution to secondary cases in Singapore,with most of the imported cases dating back to the earlyphase of the epidemic and between March 10 and 17,
2020. However, there are examples such as the Grant
Hyatt Singapore cluster and the Yong Thai Hang clusterthat were linked to imported sources, and the original

Fig. 8 The effective reproduction number reproduction number with 95% CI estimated by adjusting for the imported cases α = 0.15 during thefirst transmission wave by February 14, 2020. The effective reproduction number followed a declining trend with the latest estimate at 0.7 (95% CI
0.3, 1.0) by February 14, 2020

Tariq et al. BMC Medicine(2020) 18:166

sources had left Singapore before these local clusters
emerged [30].
Our Rt estimates for Singapore are substantially lower
than mean estimates reported for the COVID-19 epidemic in other parts of the world [57–65]. This indicatesthat containment efforts have a significant impact inSingapore (Table 2). However, some differences in the
reproduction numbers reported for the epidemic in
China may result from different methods, differences indata sources and time periods used to estimate thereproduction number. Similarly, a recent study has
shown an average reporting delay of 6.1 days in China[66] which agrees with our mean estimate for cases in
Singapore (6.4 days). Moreover, the scaling parameterfor growth rate (p) indicates a sub-exponential growth
pattern in Singapore, reflecting the effective isolationand control strategies in the region. This is consistent
with a sub-exponential growth pattern for Chinese provinces excluding Hubei (p ~ 0.67), as estimated by a recent study [67] whereas an exponential growth pattern
was estimated for Hubei (p ~ 1.0) [67].
A previous study on the 2015 MERS outbreak in South
Korea reported substantial potential for superspreading

Page 11 of 14transmission despite a subcritical reproduction number [68]. The lower estimate of the dispersion parameterin our study also indicates significant transmission heterogeneity in Singapore. Superspreading events of MERSCoV and SARS-CoV associated with nosocomial outbreaks are well documented and driven largely by substantial diagnostic delays [16]. Although the average delay
from onset of symptoms to diagnosis/reporting for
COVID-19 patients in Singapore is at 6.4 days and nosuperspreading events has been observed yet, the dispersion parameter, k < 1, indicates the probability of observing large clusters and the potential for superspreading
such as the SAFRA Jurong cluster [50, 68]. Therefore,public health measures enacted by public health authorities in Singapore that advise the public to avoid mass
gatherings and confined places are crucial to prevent disease amplification events. However, the presence ofasymptomatic cases in the community represents an ongoing threat although it is not currently known if subclinical cases are less infectious [20, 69]. This highlights theneed for rapid testing of suspected cases to quickly isolate
those that test positive for the novel coronavirus. To
achieve this goal, public health authorities in Singapore

Table 2 Timeline of COVID-19 epidemic in Singapore as of March 31, 2020 [9]
Date

Event

1/23/2020

First imported case of SARS-CoV-2 confirmed

1/23/2020–1/26/2020

Flights to Wuhan canceled by the Singaporean government

1/29/2020

Travelers from Hubei denied entry in Singapore

2/1/2020

New visitors with recent travel history to mainland China within the last 14 days denied entry into Singapore, ortransit through Singapore

2/1/2020

Distribution of masks by the government

2/4/2020

First cases of local SARS-CoV-2 transmission

2/6/2020

First recovered patient in Singapore

2/7/2020

Singapore’s outbreak response level upgraded from yellow to orange

2/17/2020

Stay at home notices issued for 14 days for all Singapore residents and long-term work pass holders returning from China

2/23/2020

Travel advisory extended to visitors from South Korea

2/25/2020

Links between Grace Assembly of God cluster and The Life Church and Missions cluster established2/26/2020

Ban on visitors arriving from Cheongdo and Daegu in South Korea.

2/28/2020

Singapore company Biotech introduced COVID-19 test kit for in vitro case diagnosis

3/4/2020

Ban implemented on visitors arriving from South Korea, Iran, and Italy

3/10/2020

600 passengers disembarked from the Italian cruise ship, Costa Fortuna and social distancing measures announced

3/12/2020

First two deaths from COVID-19 reported

3/15/2020

Ban implemented on visitors arriving from Italy, France, Spain, and Germany

3/18/2020

Announcement made for all visitors entering Singapore from March 20, 2020 onwards to observe a 14-day quarantine

3/22/2020

Ban implemented on all short term visitors arriving or transiting from Singapore from March 23, 2020 onwards

3/23/2020

Announcement made for travelers including Singapore citizens who will be required to submit a healthdeclaration before entering Singapore

3/24/2020

Social distancing measures reinforced including bans on large gatherings and social events

3/26/2020

Punishments announced for individuals breaching the stay at home notices

Tariq et al. BMC Medicine(2020) 18:166

are reactivating 900 general practitioner clinics [70]. While
new clusters emerge in Singapore, some clusters including
the Yong Thai Hang cluster, Seletar Aerospace cluster,Wizlearn Technologies, and the Grand Hyatt cluster havestabilized (no recent additional cases in most clusters).
The “Grace Assembly of God and the Life Church andMissions” cluster and the “SAFRA Jurong” cluster continue to be consolidated .
Beyond Singapore, COVID-19 cases are now being reported in 204 countries including identifiable clusters inmany parts of the world [2, 71–74]. Moreover, Singapore
has also produced secondary chains of disease transmission beyond its borders [24]. Although Singapore has
been detecting and isolating cases with diligence, ourfindings underscore the need for continued and sustained containment efforts to prevent large-scale community transmission including nosocomial outbreaks.
Overall, the current situation in Singapore highlights theneed to investigate the imported, unlinked, and asymptomatic cases that could be a potential source of secondary cases and amplified transmission in confinedsettings. Although Singapore has a world-class healthsystem including a highly efficient contact tracing mechanism in place that has prevented the outbreak from getting out of control [24, 75], continued epidemiologicalinvestigations and active case finding efforts are needed
to contain the outbreak.
Our study is not exempt from limitations. First, theoutbreak is still ongoing and we continue to monitor thetransmission potential of COVID-19 in Singapore. Second, onset dates are missing for 12 cases, which were excluded from our analyses. Third, we cannot rule out that
additional cases will be added to existing clusters, which
may lead to underestimating the reproduction number
based on the cluster size distribution. Fourth, some of
the cases are associated with generating secondary
chains in more than one cluster, which were included in
the most relevant cluster.

Conclusion
This is a real-time study to estimate the evolving transmission potential of SARS-CoV-2 in Singapore. Ourcurrent findings point to temporary sustained transmission of SARS-CoV-2, with our most recent estimate of
the effective reproduction number lying below 1.02.
These estimates highlight the significant impact of containment efforts in Singapore while at the same timesuggest the need to maintain social distancing and active
case finding efforts to stomp out all active or incoming
chains of transmission.
Abbreviations
COVID-19: Coronavirus Disease 2019; MERS: Middle Eastern Respiratory
Syndrome; SARS: Severe acute respiratory syndrome; SARS-CoV-2: Severe
acute respiratory syndrome-related coronavirus 2

Page 12 of 14

Acknowledgements
Not applicable.
Authors’ contributions
A.T, S.B., P.Y., and G.C. analyzed the data. A.T., Y.L, P.Y, and S.M. retrieved andmanaged data; A.T and G.C wrote the first draft of the manuscript. All
authors contributed to writing and revising subsequent versions of themanuscript. All authors read and approved the final manuscript.
Funding
G.C. is supported by NSF grants 1610429 and 1633381. G.C. and S.B. arepartially supported by R01 GM 130900.
Availability of data and materials
The data supporting the conclusion of this article is available from the
Ministry of Health, Singapore website [27].
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
G.C. is a Board Member for the journal. The other authors declare that they
have no competing interests.
Author details
1
Department of Population Health Sciences, School of Public Health, Georgia
State University, Atlanta, GA 30303, USA. 2F. I. Proctor Foundation, Universityof California, San Francisco, CA, USA. 3Infectious Disease Prevention andControl Branch, Public Health Agency of Canada, Ottawa, Canada.
4
Epidemiology and Disease Control Division, Public Health Group, Ministry of
Health Singapore, Singapore, Singapore.
Received: 22 February 2020 Accepted: 4 May 2020

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